Nov 9 – 13, 2015
Europe/Zurich timezone
There is a live webcast for this event.

The LHC experiments have been producing the largest amount of complex data.  100TB/s of real-time data analyses and analyses of 100 EB of data are anticipated  and planned for. The field of data science beyond statistical methods  has been producing advanced, intelligent methods for data analysis, pattern recognition and model inference. This workshop will engage the two communities towards cross exchanges and applications that can forge accelerated progress in big basic science questions. 

Some of the topics that will be addressed  include cutting edge pattern recognition methods for  elementary particle identification; intelligent detectors that learn from their failures and self-adjust to increase their performance efficiency; fast reconstruction of  charged particle tracks;  high-rate event selection algorithms that learn to select rare physics processes;  advanced data  techniques  that can guide discovery and other challenges that can profit from advanced  computational methods and resources. 

The workshop includes plenary presentations, tutorials and hands-on hackathon-type of ML exercises as well as directed and undirected discussion and brainstorming time.

Subscribe  to the participants mailing list for discussions on the topic and announcements before and during the workshop by sending email  to:

Follow the workshop official account @DataScienceLHC . Feel free to tweet using the recommended hash tag #DSLHC15

The workshop will take place at CERN, it is open to anyone with an interest on Data Science application to High Energy Physics. There are no fees but registration for attendance in person is necessary for organization purposes. Registration for non-CERN users is prerequisite in order to gain access to the CERN site during the workshop.

Registration is closed at this time. However, the event will be in video conference and on CERN webcast.

For accommodation and access to CERN as well as laptop registration, check the registration page